In 2015, the United States spent $3.2 trillion on healthcare, amounting to an astounding 17.8 percent of GDP and roughly $10,000 per citizen. A substantial portion of American healthcare spending — more than $323 billion in 2016 — goes to covering the cost of prescription drugs.

It makes sense, then, that the pharmaceutical industry — which accounts for nearly 2 percent of the country’s annual economic activity — is unparalleled in its complexity when considered alongside other powerhouse industries like retail, manufacturing, professional services, and even real estate. While each is complex in its own right, marketers within the pharmaceutical sphere face a formidable set of challenges when it comes to communicating with consumers — and tracking their conversions.

Why? There are several unique factors at play within the American healthcare ecosystem that simply do not arise in traditional consumer marketing. Not only are the stakes involved in pharmaceutical marketing ratcheted up to the level of literal life and death, but the underlying market architecture often more closely resembles an M.C. Escher image than a straight line from producer to consumer.

But that same complexity is what makes the healthcare industry a fascinating opportunity for marketers who are up for a challenge — particularly from a data analytics perspective. Let’s explore why.

Opaque “purchasing” decisions

Unlike most products and services, purchasing decisions relating to prescription pharmaceuticals almost never fall exclusively to the end consumer (i.e. a patient). A patient’s healthcare provider (HCP) typically has the most direct control over whether Drug A gets prescribed instead of Drug B, but insurance companies and government agencies — Medicare, Medicaid, the VA — often exert influence, as well.

Of course, patients are not entirely powerless; each of us has the ability to “ask our doctor about” this drug or that drug that we saw advertised on television or encountered when surfing WebMD. For marketers, the problem is that such queries take place entirely offline. It’s effectively impossible to tie a specific ad impression — whether delivered online, on TV, or elsewhere — to a patient question, let alone to a conversion (i.e. an HCP prescribing decision). The connection between an ad campaign for a particular drug and a spike in the drug’s popularity may very well be there, but it’s difficult to definitively establish causality like they can in, say, an ecommerce environment where a click on a banner ad leads directly — and, critically, “traceably” — to a purchase.

In any other industry, marketers are likely accustomed to communicating with consumers who not only have more control over a purchasing decision, but are also more readily identified along the digital path to purchase — whether on-site or on social platforms. In healthcare settings, marketers face the fascinating — and, depending on who you ask, exciting — challenge of bridging the disconnect between consumer’s online and offline behavior.

Multilayered decision structures

Pharmaceutical purchasing decisions are often not only taken out of an individual patient’s hands, but out of an individual HCP’s hands, as well.

Almost a third (32 percent) of U.S. healthcare spending goes toward treatment provided in a hospital setting, and prescription drug costs account for the third largest expense category (6.9 percent of their budgets) for American hospitals. However, generally speaking, neither HCPs nor even hospital boards have the freedom to make pharmaceutical purchasing decisions on their own, as group purchasing organizations (GPOs) continue to be the dominant players in the American pharmaceutical supply chain.

In short, GPOs enable hospitals — especially smaller ones — to secure bulk-buying prices and supply chain efficiencies that would otherwise be out of reach by aligning their purchasing activities with the purchasing activities of other GPO members. According to the Healthcare Supply Chain Association, purchasing pharmaceuticals via a GPO can save a hospital between 10 percent and 15 percent every year, amount to annual industry-wide savings of $33 billion. It’s not surprising, then, that some 97 percent of American hospitals are affiliated with at least one GPO.

Similarly, hospitals and other care facilities leverage the power of aggregative purchasing by forming integrated delivery networks (IDNs). An IDN brings diverse healthcare providers from across the entire care continuum under one operating umbrella, standardizing their pharmaceutical practices — in terms of treatment protocols, product preferences and procurement practices.

As such, pharmaceutical companies can differentiate their products — and improve representation in a physician’s formulary — by addressing the needs of various stakeholders within a health system. Cost continues to be a primary consideration — a price difference of as little as 5 or 10 cents per unit can make a substantial difference when multiplied out across thousands of units. But, as we know, improving patient outcomes and safety within the hospital setting also ranks high on the list of product attributes to consider, and pharmaceutical manufacturers can infuse relevant messaging based on the specific concerns of their end users.

At first blush, GPOs and IDNs may appear to be a major obstacle to effective, personalized HCP messaging. These networks are neither monolithic nor, in truth, particularly susceptible to advertising, and represent a collection of targets with varying degrees of power across any given network. But with a little creativity in how we gather and activate network data — key decision-makers within each network, physician affiliations, and prescribing data — it’s possible for pharmaceutical marketers to create hyper-targeted outreach tailored to the historical and anticipated preferences of a given organization.

What the future looks like

The pharmaceutical marketing landscape is undeniably labyrinthine — the end consumers, patients, are “hidden” behind HCPs, who are often hidden behind hospital boards, who are hidden behind GPOs and IDNs — but this doesn’t mean that the whole effort is futile. The mass digitization of healthcare, in particular, is providing pharmaceutical marketers with an unprecedented opportunity to speak to each of these consumer segments in new and exciting ways.

The challenge — and, ultimately, the opportunity — for pharmaceutical marketers moving forward will be to find ways to navigate the complex distribution of buying power within the healthcare space, which increasingly calls for an account-based, B2B, and above all, data-driven outreach model. It’s impossible for one marketer or team of marketers to effectively blanket all of the diverse parties involved in the pharmaceutical path the purchase. But when dedicated marketers work in tandem, leveraging datasets in order understand bite-sized chunks of the larger industry landscape, the opportunities for collaboration, creativity, and innovation are unparalleled across other industries.

That’s not to say pharma marketing will ever be a walk in the park — it won’t. But marketers capable of creatively leveraging data to tackle traditional “barriers” to success? They’ll not only to move more units, but empower customers to meet shared goals and improve patient outcomes.

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I lead the Analytics & Data Science practice at Saatchi & Saatchi Wellness. I have focused my career within the healthcare marketing analytics space, empowering healthcare marketers with data-driven strategic guidance while developing innovative solutions to healthcare marketing problems through the power of data science.
I’ve worked to measure, predict, and optimize marketing and business outcomes across personal, non-personal, digital, and social channels. I’ve led engagements with brands that span all stages of the product lifecycle, with a particular focus on established brands.
My role is to guide the departmental vision and lead innovation initiatives, effectively positioning marketing analytics as a competitive differentiator and organic growth driver for the agency at large.